A Hybrid Web-Based and In-Person Self-Management Intervention to Prevent Acute to Chronic Pain Transition After Major Lower Extremity Trauma (iPACT-E-Trauma): Protocol for a Pilot Single-Blind Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Acute pain frequently transitions to chronic pain after major lower extremity trauma (ET). Several modifiable psychological risk and protective factors have been found to contribute to, or prevent, chronic pain development. Some empirical evidence has shown that interventions, including cognitive and behavioral strategies that promote pain self-management, could prevent chronic pain. However, the efficacy of such interventions has never been demonstrated in ET patients. We have designed a self-management intervention to prevent acute to chronic pain transition after major lower extremity trauma (iPACT-E-Trauma). OBJECTIVE: This pilot randomized controlled trial (RCT) aims to evaluate the feasibility and research methods of the intervention, as well as the potential effects of iPACT-E-Trauma, on pain intensity and pain interference with daily activities. METHODS: A 2-arm single-blind pilot RCT will be conducted. Participants will receive the iPACT-E-Trauma intervention (experimental group) or an educational pamphlet (control group) combined with usual care. Data will be collected at baseline, during iPACT-E-Trauma delivery, as well as at 3 and 6 months post-injury. Primary outcomes are pain intensity and pain interference with daily living activities at 6 months post-injury. Secondary outcomes are pain self-efficacy, pain acceptance, pain catastrophizing, pain-related fear, anxiety and depression symptoms, health care service utilization, and return to work. RESULTS: Fifty-three patients were recruited at the time of manuscript preparation. Comprehensive data analyses will be initiated in July 2017. Study results are expected to be available in 2018. CONCLUSIONS: Chronic pain is an important problem after major lower ET. However, no preventive intervention has yet been successfully proven in these patients. This study will focus on developing a feasible intervention to prevent acute to chronic pain transition in the context of ET. Findings will allow for the refinement of iPACT-E-Trauma and methodological parameters in prevision of a full-scale multi-site RCT. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 91987302; http://www.controlled-trials.com/ISRCTN91987302 (Archived by WebCite at http://www.webcitation.org/6rR8G2vMs).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".